Apparatus and imaging method with synthetic aperture for determining an incident angle and/or a distance

ABSTRACT

The invention relates to an imaging method with synthetic aperture for determining an incident angle and/or a distance of a sensor from at least one object in space, wherein at each of a number of aperture points one echo profile is sensed. Advantageously, for several angles assumed as the incident angle, one phase correction value and/or one distance correction value is calculated, adapted profiles are generated based on the echo profiles by adapting the phase with the phase correction value for each assumed angle and/or by shifting the distance with the distance correction value, for the assumed angle, the adapted profiles are summed or integrated, and a probability distribution is derived, and a probability value for the incident angle and/or for the distance is determined therefrom. A determination of the incident angle is also possible independently of the distance, wherein it is possible to only consider velocities or accelerations.

CROSS-REFERENCE TO RELATED PATENT APPLICATION

This application claims the benefit of German Patent Application No. 10 2009 030 075.9, filed on Jun. 23, 2009, in the German Patent Office, the disclosure of which is incorporated herein in its entirety by reference.

BACKGROUND

The invention relates to an imaging method with synthetic aperture for determining an incident angle and/or a distance of a sensor from at least one object or transponder in space wherein, at a number of aperture points, one respective echo profile is sensed, or a related apparatus therefor.

So-called SA systems (SA: Synthetic Aperture) are generally known, the use of which is exhaustively explained, for example, in “H. Radar with Real and Synthetic Aperture” Clausing and W. Holpp, Oldenbourg, 2000, chapter 8, pp. 213 and the following, or in M. Younis, C. Fisher and W. Wiesbeck, “Digital beamforming in SAR systems”, Geoscience and Remote Sensing, IEEE Transactions on, vol. 41, pp. 1735-1739, 2003 for a microwave range. The use of SA methods is also known, for example, from International Patent Publication No. WO 2006/072471, German Patent Document No. DE 199 10 715 C2 or European Patent Document No. EP 0 550 073 B1. In the field of so-called radar sensorics, SAR (Synthetic Aperture Radar) or even SDRS (Software-Defined Radar Sensors) are used as names in this context.

Almost identical methods have long been known in the field of medicine or ultrasonic measuring technology, under the names holography, or tomography. Descriptions of the latter methods can be found, for example, in M. Vossiek, V. Magori, and H. Ermert, “An Ultrasonic Multielement Sensor System for Position Invariant Object Identification”, presented at the IEEE International Ultrasonics Symposium, Cannes, France, 1994, or in M. Vossiek, “An Ultrasonic Multi-transducer System for Position-independent Object Detection for Industrial Automation”, Fortschritt-Berichte VDI, Reihe 8: Mess-, Steuerungs- and Regelungstechnik, vol. 564, 1996.

It is generally known that SA methods can be carried out with all coherent waveforms, such as in the radar range, with electromagnetic waves, and with acoustic waves, such as ultrasonic waves, or with coherent light. SA methods can also be carried out with any non-coherent waveform that is modulated with a coherent signal form.

SA methods are also used in systems in which a wave-based sensor measures a cooperative target, such as a coherently reflecting backscatter transponder. Examples and descriptions can be found in German Patent Document DE 10 2005 000 732 A1 and in M. Vossiek, A. Urban, S. Max, P. Gulden, “Inverse Synthetic Aperture Secondary Radar Concept for Precise Wireless Positioning”, IEEE Trans. on Microwave Theory and Techniques, vol. 55, issue 11, November 2007, pp. 2447-2453.

The fact that signals from wave sources, whose characteristic and coherence is not known to the receiver, can be processed by way of SA methods if at least one signal is formed from at least two signals received in a spatially separated manner, which no longer describes the absolute phase but phase differences of the signals, is known, for example, from German Patent Document DE 195 12 787 A1. In this case, a signal emanating from an object or emitted by a transponder can be sensed by two receivers arranged at a known distance with respect to each other, wherein the phase difference between these two signals can be used in further evaluation. Transponder systems in the previously shown arrangement variant for which a principle explained in the following is suitable, are, for example, secondary radar systems, as they are explained, in particular, in German Patent Documents DE 101 57 931 C2, DE 10 2006 005 281, DE 10 2005 037 583, Stelzer, A., Fischer, A., Vossiek, M.: “A New Technology for Precise Position Measurement-LPM”, In: Microwave Symposium Digest, 2004, IEEE MTT-S International, vol. 2, 6-11 Jun. 2004, pp. 655-658, R. Gierlich, J. Huttner, A. Ziroff, and M. Huemer, “Indoor positioning utilizing fractional-N PLL synthesizer and multi-channel base stations”, Wireless Technology, 2008, EuWiT 2008, European Conference on, 2008, pp. 49-52., or S. Roehr, P. Gulden, and M. Vossiek, “Precise Distance and Velocity Measurement for Real Time Locating in Multipath Environments Using a Frequency-Modulated Continuous-Wave Secondary Radar Approach”, IEEE Transactions on Microwave Theory and Techniques, vol. 56, pp. 2329-2339, 2008.

The high precision knowledge of sensing positions, that is the positions of the so-called aperture points, has turned out to be particularly problematic for implementing the SAR methods in technological products. A wavelength is about 5 cm in a 5.8 GHz radar signal. For the relative measurement of the aperture, a measuring error is needed that is substantially smaller than the wavelength of the waveform used, e.g., smaller than a tenth of the wavelength. This cannot be sufficiently achieved or can only be achieved with difficulty with technologically simple approaches, such as with simple odometers, wheel sensors, rotation sensors, so-called encoders, acceleration sensors, etc, in particular across larger movement trajectories or longer measuring times. The calculation of distance data from velocity or acceleration values entails the problem, in particular, that measuring errors integratively accumulate due to the necessary integration of measuring quantities, and the measuring errors strongly increase as the size of an integration interval increases.

A drawback of SA methods is, moreover, that SA methods usually have a very high computation overhead and an image function must be calculated both in the distance direction and in the angular direction, or in all space coordinates of the object space. The calculation is also necessary if only one coordinate, such as only one incident angle, is of interest.

In the use of known methods for distance measurement a highly precise position measurement is necessary for determining aperture points, wherein it is disadvantageously required that a measuring error of the position measurement must be substantially smaller than a wavelength of the incident wave.

SUMMARY

It is the object of various embodiments of the invention to enhance an imaging method with synthetic aperture for determining an incident angle and/or a distance of a sensor from at least one object or transponder in space, or an apparatus therefor. In particular, determination of an incident angle is to be enabled without reliance on a distance from the object or transponder.

This object is achieved by an imaging method with synthetic aperture for determining an incident angle and/or a distance of a sensor from at least one object or transponder in space with the features described below, or by an apparatus therefor with the features described below. Advantageous embodiments are also described in more detail below.

In particular, an imaging method with a synthetic aperture for determining an incident angle and/or a distance of a sensor from at least one object in space is preferred, wherein, at a number of aperture points, one respective echo profile is sensed, if one phase correction value and/or one distance correction value is calculated for each of a plurality of assumed angles as the at least one incident angle, adapted profiles are generated on the basis of the echo profiles by adapting the phase by the phase correction value for each of the assumed angles and/or by shifting the distance by the distance correction value, a probability distribution is formed for the assumed angles from the adapted profiles, and a probability value for the incident angle and/or the distance is determined from the probability distribution.

The probability distribution thus gives an indication on whether the assumed angle corresponds to the actual incident angle, or whether the distance value corresponds to the unknown actual distance.

For the assumed angles, the adapted profiles are preferably summed up or integrated. The probability distribution is formed therefrom. In particular, phase correction values and/or the distance correction values are calculated on the basis of the aperture points from the position data of the aperture.

According to a first variant, an adapted echo profile is generated as the adapted profile by adapting the phase of the echo profiles for each assumed angle by the phase correction value and/or shifting the distance by the distance correction value.

By summing up or by determining maxima, the probability function can be separated into one-dimensional probability functions. It is thus possible, in particular, to form probability functions independently from each other, also for only the angle determination or for only the distance determination.

Preferably a number of phase velocity profiles are formed from the echo profiles, and phase angle velocities are determined as their argument. Their phase characteristic advantageously provides an indication on a distance change, or a radial velocity. The number can be created by considering directly adjacent echo profiles, each time, principally, however, by any other combinations of non-adjacent echo profiles.

Preferably the at least one angle assumed as the incident angle is calculated in dependence on a relative movement velocity between the wave-based sensor and the object and, in each case, one complex phase correction value is calculated as a correction in dependence on a phase variation based on a velocity difference. This enables the comparison of data from a velocity sensor system instead of data from a distance sensor system. In this way, the otherwise high aperture sensor system requirements are advantageously made less demanding.

Preferably, for each assumed angle, the phase corrected phase velocity profiles are summed up or integrated to form velocity probability density functions. Their real portion, in particular, gives an indication on whether the assumed angle corresponds to the actual incident angle.

A method is preferred, in particular, wherein the at least one angle assumed as the incident angle is calculated in dependence on a relative acceleration between the wave-based sensor and the object, and, in each case, one complex phase correction value is calculated as a correction in dependence on a phase variation based on an acceleration difference. This enables a comparison of data of a velocity sensor system instead of data of a distance sensor system. In this way, the otherwise high aperture sensor system requirements are advantageously made less demanding. A determination of the incident angle is made possible, in particular, also without relying on the distance. The particular advantage of the acceleration-based method is that in practice it is much easier to measure accelerations with small drift errors than velocities or distances. This advantage can be implemented, in particular, in hand-held radio systems.

Herein, a number of phase acceleration profiles can be formed from the echo profiles and a vectorial acceleration can be determined as their argument. Their phase characteristic advantageously gives an indication on velocity changes or radial accelerations. In particular, for each assumed angle, the phase corrected phase acceleration profiles can be summed up or integrated to form an acceleration probability distribution. In particular, their real portion gives an indication on whether the assumed angle corresponds to the actual incident angle.

Herein, an analytical calculation of the extreme values of the one-dimensional acceleration probability distribution or of the zero crossing of the phase of the one-dimensional acceleration probability distribution can be carried out. This results in a substantial reduction of the computation overhead. The thus possible determination of the incident angle and the distance on the velocity and acceleration level has the advantage that the systematic errors accumulating over time and/or distance, of the relative sensor system, have no weight or have considerably less weight, and the uniqueness range is increased.

For sensing the echo profile, a signal can be transmitted from the sensor to the at least one object, and the at least one object in space includes a transponder, or is configured as a transponder, which receives the signal and, in dependence on the signal, transmits a modified signal as a signal coming from the object, back to the sensor, which is used as a signal received in the sensor as the echo profile.

As an independent aspect, an apparatus is advantageous with a wave-based sensor for sensing a sequence of echo signals of an object, and with a logic and/or with a processor accessing at least one program as a controller, wherein the logic and/or the processor are configured for carrying out such an advantageous method for determining an incident angle and/or a distance of a sensor from at least one object in space.

In particular, such an apparatus is equipped with a memory or an interface to a memory, wherein the program is stored in the memory. In a manner known as such, such an arrangement can comprise hardware components as the logic, which can be adapted for running necessary programs via suitable wiring or an integrated structure. The use of a processor including a processor of a computer connected, for example, via an interface, can also be implemented for carrying out a suitable program that is stored in an accessible manner. Combined approaches of fixed hardware and a processor are also possible. The object can comprise a transponder or be configured as a transponder.

DESCRIPTION OF THE DRAWINGS

An advantageous embodiment will be explained in the following with reference to the drawing in more detail, wherein:

FIG. 1 shows an exemplary measuring arrangement, and

FIG. 2 shows an exemplary method step sequence for an imaging method with synthetic aperture for determining an angle and a distance of an object,

FIG. 3 shows a preferred sequence of method steps for an imaging method for determining an angle and a distance of an object, and

FIG. 4 shows exemplary signal characteristics in the context of carrying out this preferred sequence of method steps.

DETAILED DESCRIPTION

As can be seen in FIG. 1, a signal s is transmitted by an apparatus V by way of a signal source. The transmitted signal s is reflected on an object O at a distance from the sensor S. The signal reflected by the object O propagates as a signal rs coming from the object O in the direction toward a sensor S. The sensor S is preferably arranged or formed in or on the apparatus V, which also comprises the signal source. Preferably the apparatus will be configured both as a transmitter and a receiver, so that, in terms of tolerances, an identical location can be assumed for the transmitter and the receiver.

This arrangement is present in a space that can be defined by any reference coordinate system. A Cartesian coordinate system with orthogonal space coordinates x, y, z is shown for illustrative purposes only. An imaginary connecting line, along which the signal S or its wave propagates to the object O and along which the signal rs or its wave coming from the object O propagates, extends at an oblique angle to the extension of the space coordinates, wherein, for simplicity, only two of the Cartesian space coordinates x, y are shown. This angle thus corresponds to an incident angle φ_(R) of the planar waves with respect to the reference coordinate system.

Optionally, the signal rs coming from the object O can also come from an actively transmitting transponder, which is arranged on the object O or which is present as the object O itself at the position of such an object O. Preferably, the object O can thus have a transponder or be configured as a transponder.

For deriving a preferred approach, a classical SAR aperture is assumed, for example, as it is shown in FIG. 1. Only for purposes of simplified explanation and without excluding a generalization, the following assumptions are made for further applications:

The object O is present at an object position p({right arrow over (r)}) wherein {right arrow over (r)}=(x,y) as a radial space coordinate in the Cartesian coordinate system.

A number of Q measurements at Q aperture points {right arrow over (α)}_(q)=(x_(aq),y_(aq))^(T) is carried out with the aid of the sensor S in the direction toward the object O (wherein q=1, 2, . . . , Q).

Each of the Q measurements results in an echo profile sig_(q)(d) as a measuring system with, for example, in the case of a single object O, a distance d as an instantaneous object distance of the object from sensor S. These echo profiles sig_(q)(d) should have complex values, so that the following applies: sigq(d)=|sigq(d)|e ^(j·arg{sig) ^(q) ^((d)}), wherein arg{sig_(q) (d)} is a phase angle φ_(q)(d)=arg{sig_(q) (d)} of the complex signal, i.e. of the echo profile sig_(q)(d) having complex values. Expressed in a generalized manner, an echo profile sig_(q)(d) is comprised of a plurality of received signals, which have propagated from one or more objects O not only via one respective direct path, but as the case may be, also via indirect paths and thus different signal paths to the sensor S arriving at a delayed time.

If the measuring signals have real values, they are preferably to be extended to signals having complex values by way of a Hilbert transformation.

The object O should be so far removed from the synthetic aperture that it can be expected that the wave emitted by the object O can be assumed as a planar wave at the location of the aperture. The assumption of planar waves is valid if a distance d_(R) between the sensor S and the object O corresponds to a minimum distance, which allows a parallel wave characteristic to be approximated from the point of view of a plurality of measuring positions.

This condition can be deemed as fulfilled if a change in the distance of the transmission path from the sensor S to the object O, which is due to a lateral distance Δd_(q)(φ_(R)) of the aperture points {right arrow over (α)}_(q)=(x_(aq),y_(aq))^(T) transverse to the wave propagation direction, is small with respect to a wavelength λ of the signal s, rs, i.e. if the following applies: √{square root over (d _(R) ²(Δα_(q)·sin(β_(q)−φ_(R)))²)}−d _(R)<<λ, wherein Δα_(q) is an actual distance between aperture points {right arrow over (α)}₁, {right arrow over (α)}_(q) with respect to each other and β_(q) is a reference angle for these aperture points {right arrow over (α)}₁, {right arrow over (α)}_(q), between the Cartesian coordinate system and any reference coordinate system, in which the incident angle φ_(R) of the planar wave is considered.

A distance from the first aperture point d, to the object O at the object position p({right arrow over (r)}) with {right arrow over (r)}=(x,y)^(T) is chosen as a reference distance d_(R) from object O to the aperture. Basically, however, the choice is arbitrary. Thus the following applies: d _(R)=√{square root over ((x _(a1) −x)²+(y _(a1) −y)²)}{square root over ((x _(a1) −x)²+(y _(a1) −y)²)}.

Based on this assumption, a reconstruction formula is derived:

From the assumption with respect to a planar wave propagation, it follows that a distance change as the lateral distance Δd_(q)(φ_(R)) of the transmission path from the sensor S to the object O, because of the movement of the sensor 0 from the first aperture point {right arrow over (α)}₁ to the last aperture point {right arrow over (α)}_(q), is no longer dependent on the instantaneous distance d to the object O but only on the positions of the aperture points {right arrow over (α)}₁, {right arrow over (α)}_(q) and the incident angle φ_(R) of the planar wave. The following relationships thus apply:

${\Delta\; a_{q}} = \sqrt{\left( {x_{aq} - x_{a\; 1}} \right)^{2} + \left( {y_{aq} - y_{a\; 1}} \right)^{2}}$ Δ d_(q)(φ_(R)) = Δ a_(q) ⋅ cos (β_(q) − φ_(R)) ${\cos\left( \beta_{q} \right)} = \frac{x_{aq} - x_{a\; 1}}{\Delta\; a_{q}}$ with

Δ_(q), β_(q) can be determined and derived in a manner mathematically known as such with methods for distance determination. In the following, a simplification of the method for the separate computation of the incident angle and the distance will be shown.

The incident angle φ_(R) is an initially unknown angle, at which the target, here the object O from the point of view of the sensor S, is seen. The assumed angle φ_(RA), introduced in the following, is an assumed angle, wherein the assumed angle φ_(RA) is an arbitrary assumption whose plausibility is then tested in the following.

Consequently, at first, the unknown incident angle φ_(R) is to be determined. This problem is solved by taking measuring values of a wave-based sensor system together with measuring values of a movement sensor system, i.e. the measuring values of a position sensor system or a velocity sensor system or an acceleration sensor system for several assumed angles φ_(RA), and the plausibility is tested via these algorithms, whether or not the angle hypothesis is true for this assumed angle φ_(RA). Several advantageous methods for solving this problem will be presented in the following.

Based on the assumptions mentioned and with the aid of the geometric relationships, a sum profile can be formed from the number Q of all measured complex-valued echo profiles sig_(q)(d) for each assumed angle φ_(RA). For this purpose, at first, in a shifting step, each signal, or echo profile sig_(q)(d) is shifted by an amount of an assumed lateral distance −Δd_(q)(φ_(RA)), thus shifted echo profiles sig _(q)(d,φ _(RA))=sig _(q)(d−Δd _(q)(φ_(RA))) are formed.

This shifting step can be dispensed with, if it is true that c/B>>Δd_(q)(φ_(RA)), with B as the measuring signal bandwidth of the signals s, rs, and c as the propagation velocity of the signals s, rs or the wave. This also applies if the width of an echo signal envelope of a single echo peak, or a single measuring path of such an object O is substantially greater than the assumed lateral distance Δd_(q)(φ_(RA)) or, in other words substantially greater than the shift of echoes of the signal S on the object O, which is due to the movement of the sensor S from the aperture point {right arrow over (α)}_(q) to the aperture point {right arrow over (α)}_(q+1), which is sometimes the case with small synthetic apertures.

In a subsequent phase adaptation step, the phases of the shifted signals, or the shifted echo profiles sig_(q)(d,φ_(RA)) are adapted to a changed delay, to result in adapted echo profiles sig _(q)(d,φ _(RA))″=sig _(q)(d,φ _(RA))′·e ^(−j·ƒ(Δd) ^(q) ^((φ) ^(RA) ⁾⁾.

The function ƒ(Δd_(q)(φ_(RA))) describes a linear relationship between a signal phase change in dependence on the instantaneous distance d_(q) of the aperture point {right arrow over (α)}_(q) to the object O. The following applies:

${{f\left( {\Delta\;{d_{q}\left( \varphi_{RA} \right)}} \right)} = {{{{{const}.} \cdot \frac{\omega}{c}}\Delta\;{d_{q}\left( \varphi_{RA} \right)}} = {{{{const}.} \cdot \frac{2\pi}{\lambda}}\Delta\;{d_{q}\left( \varphi_{RA} \right)}}}},$ wherein ω is a circle center frequency of the waveform used, i.e. the signals s, rs, and c* is the phase velocity and const. is a real-value constant that depends on each measuring principle. In the time-of-arrival method, known as such, this constant has, for example, the value 1, whereas for primary radars which determine the so-called round-trip-time-of-flight, it has the value 2, and for quasi phase coherent systems a value of 4 resulted.

By summing up the Q phase-corrected or adapted echo profiles sig_(q)(d,φ_(RA))″ in a summing step, a sum profile sumsig(d,φ_(RA)) can be calculated based on all aperture points {right arrow over (α)}_(q) for each space direction, or for each assumed angle φ_(RA), according to:

${{sumsig}\left( {d,\varphi_{RA}} \right)} = {\sum\limits_{q = 1}^{Q}{{sig}_{q}\left( {d,\varphi_{RA}} \right)}^{''}}$

This is thus a two-dimensional image function, wherein the amount W(d,φ _(RA))=|sumsig(d,φ _(RA))| is a measure for the probability W(d,φ_(RA)) that an object O is present at the location (d,φ_(RA)). If a real object O is thus at the position (d,φ_(R)), the function of the measure for the probability W(d,φ_(RA)), at least if there have been no other interferences in the measurement, has a maximum at the position (d=d_(R), φ=φ_(R)). By the position of the maxima in the image function, thus both the unknown incident angle of the planar wave φ_(R) and the unknown distance d_(R) from objects O or transponders as objects O can be determined.

In summary, a first advantageous method, also illustrated in FIG. 2, can be described as follows:

In a first step S1, basic parameters are set, such as the serial index q for 1, 2, . . . , Q is set at the value 0. In a second step S2, the value of the serial index q is incremented by 1.

In a third step S3, the sensor S is moved to the aperture point {right arrow over (α)}_(q) corresponding to the instantaneous serial index q. In the next step S4, a measurement is carried out at this aperture point {right arrow over (α)}₁. As long as the serial index q is smaller than the maximum, or setpoint number of aperture points {right arrow over (α)}_(q), the process jumps back to second step S2 in a step S5.

In this manner, in the first steps S2- S5, measurements are carried out at a number Q of different aperture points {right arrow over (α)}_(q). Herein, the positions of the aperture points {right arrow over (α)}₁ are detected or determined by way of a position sensor system, unless the positions of the aperture points {right arrow over (α)}_(q) are not known a priori. In the present case, the term aperture points {right arrow over (α)}_(q) is used synonymously to the position of a measurement of the individual points of the aperture.

Each of the Q measurements results in an echo profile sig_(q)(d,φ_(R)), or is stored as such.

For several angles φ_(RA) as incident angles, in a following step S6, one distance correction value Δd_(q)(φ_(RA)) and one phase correction value f(Δd_(q)(φ_(RA))) is created based on the aperture point data, i.e. the position data of the aperture, which are calculated, for example, from data of a position sensor system. Optionally, the entire angular range is scanned in a grid and calculated for the angle φ_(RA).

The choice of the assumed angles φ_(RA) can be arbitrary, wherein an equidistant angular spacing is used across a space range of interest.

Each echo profile sig_(q)(d,φ_(R)) is adapted for each assumed angle φ_(RA) at least with respect to the phase with the phase correction value f(Δd_(q)(φ_(RA))), and if necessary, also shifted with respect to the distance with the distance correction value Δd_(q)(d,φ_(RA)), and thus a phase corrected, or adapted echo profile sig_(q)(d,φ_(RA))″ is formed in a subsequent step S7.

In a subsequent step S8, all such phase corrected echo profiles sig_(q)(d,φ_(RA))″ are summed up for each of the angles φ_(RA) assumed as the incident angles, and an image function, or a probability distribution is derived, that gives an indication on whether the assumed angle φ_(RA) corresponds to the actual incident angle φ_(R) or on which distance value d corresponds to the unknown distance d_(R).

If it is assumed that two objects O are not at the same distance or at the same incident angle φ_(R) in the object scene, in a subsequent step S9, this two-dimensional function can be separated into two one-dimensional functions, to arrive at

${W\left( \varphi_{RA} \right)} = {\max\limits_{d}{{{sumsig}\left( {d,\varphi_{RA}} \right)}}}$ or  else W(φ_(RA)) = ∫_(d = 0)^(d_(max))sumsig(d, φ_(RA))𝕕𝕕. as a measure for the probability W(φ_(RA)) of the incident angle φ_(R), or:

${W(d)} = {\max\limits_{\varphi_{RA}}{{{sumsig}\left( {d,\varphi_{RA}} \right)}}}$ or  else W(d) = ∫_(φ_(R) = 0)³⁶⁰sumsig(d, φ_(RA))𝕕φ_(RA) as a measure for the probability W(d) for the instantaneous distance d to the object O. In a subsequent step S10, the incident angle φ_(R) or the instantaneous distance d are thus determined.

If it is now assumed that the echo profiles sig_(q)(d) measured for the distance and thus also the sum profile sumsig(d,φ_(RA)) are discrete scanning signals, the integral transitions to a simple sum. Under the assumption that the echo profiles sig_(q)(d,φ_(R)) are represented by N scanning points in each case in the distance range from, for example, 0 to d_(max), the following applies:

${W\left( \varphi_{RA} \right)} = {\max\limits_{n = {1\mspace{14mu}\ldots\mspace{14mu} N}}{{{sumsig}\left( {d_{n},\varphi_{RA}} \right)}}}$ or  else $\begin{matrix} {{W\left( \varphi_{RA} \right)} = {{\sum\limits_{n = 1}^{N}{{sumsig}\left( {d_{n},\varphi_{RA}} \right)}}}} \\ {= {{{\sum\limits_{n = 1}^{N}{\sum\limits_{q = 1}^{Q}{{{sig}_{q}\left( {d_{n} - {\Delta\;{d_{q}\left( \varphi_{RA} \right)}}} \right)}{\mathbb{e}}^{{- j} \cdot {f{({\Delta\;{d_{q}{(\varphi_{RA})}}})}}}}}}}.}} \end{matrix}$

This term is particularly advantageous if a biunique determination of the distance d_(n), such as with RFID systems, is not possible due to a small uniqueness range of the carrier wave. However, it is then possible with the aid of the above-described method, only to estimate the angle, at which the RFID tag (radio frequency identification tag) is seen as a transmission point of the signal rs coming from the object O, without having to calculate the precise distance.

FIG. 3 shows a particularly preferred sequence of method steps, wherein phase velocity profiles sig_(vq)(d) are formed from the echo profiles sig_(q)(d), and evaluated. Herein, the first method steps S1-S5 are identical to the sequence of method steps according to FIG. 2.

Under the assumption that the angle range covered by the assumed angle (P_(RA) is subdivided in K discrete angle values φ_(RAK), the following applies:

${W(d)} = {\max\limits_{k = {{1\mspace{14mu}...}\mspace{14mu} K}}{{{sumsig}\left( {d,\varphi_{RAk}} \right)}}}$ or  else ${W(d)} = {{{\sum\limits_{k = 1}^{K}\;{{sumsig}\left( {d,\varphi_{Rk}} \right)}}}.}$

However, a very precise position measurement is not needed, at least if the preferred embodiment according to FIG. 2 is applied for determining the aperture points in the present case. In particular, it is not absolutely necessary that the measuring error of the position measurement be significantly smaller than the wavelength of the incident wave.

It is now possible, from the number Q of echo profiles sig_(q)(d), the phase characteristic of which is usually a linear function of the distance d, to form a number Q−1 of phase velocity profiles sig_(vq)(d), the phase characteristic of which gives an indication on the distance change, i.e. on the radial velocity. The phase velocity profiles sig_(vq)(d) are formed in a step S6 a*, by forming the difference of two echo profiles sig_(q)(d), sig_(q−1)(d) for each phase value, and by multiplying it with the amplitude of the distance value. The two echo profiles sig_(q)(d), sig_(q−1)(d) are preferably, but not necessarily, two adjacent echo profiles sig_(q)(d), sig_(q−1)(d). Any difference pairs can be formed for this purpose, while adjacent ones will be used in the following explanations, by way of example. A phase angle velocity φ_(q)(d) or, in other words, the argument arg{sigv_(q)(d)} of the phase velocity profiles sig_(vq)(d), results in:

${{\omega_{q}(d)} = \frac{{\varphi_{q}(d)} - {\varphi_{q - 1}(d)}}{\Delta\; T_{q}}},$ wherein ΔT_(q) is a time interval having elapsed between a measurement having the index q−1 and a measurement having the index q at the two aperture points {right arrow over (α)}_(q−1) and {right arrow over (α)}_(q), respectively. If the measurements are made at constant time intervals, ΔT_(q) is constant.

The phase velocity profiles sig_(rq)(d) can preferably be calculated as follows: h _(vq)(d)=sig _(q)(d)·sig _(q−1)(d)*, wherein the phase angle velocity results in:

${\omega_{q}(d)} = \frac{\arg\left\{ {h_{vq}(d)} \right\}}{\Delta\; T_{q}}$ and the phase velocity profiles sig_(vq)(d) are defined as sig _(vq)(d)=|h _(vg)(d)|·e ^(j·ω) ^(α) ^((d)).

To avoid squaring of the signal amplitudes, the following could also be formulated:

${{sig}_{vq}(d)} = {\sqrt{{h_{vq}(d)}} \cdot {\mathbb{e}}^{j \cdot {\omega_{q}{(d)}}}}$ or sig_(vq)(d) = sig_(q)(d) ⋅ 𝕖^(j ⋅ ω_(q)(d)) or sig_(vq)(d) = sig_(q − 1)(d) ⋅ 𝕖^(j ⋅ ω_(q)(d)) or ${{sig}_{vq}(d)} = {\frac{1}{2}{\left( {{{{sig}_{q - 1}(d)}} + {{{sig}_{q - 1}(d)}}} \right) \cdot {{\mathbb{e}}^{j \cdot {\mathbb{e}}^{j \cdot {\omega_{a}{(d)}}}}.}}}$

The concrete characteristic of the contributions is not critical, for further processing, so that other combinations or even constant or arbitrarily assumed amounts could also be used. The five previously shown variants are physically applicable and therefore to be understood as a preferred exemplary embodiment.

Advantageously, a holographic reconstruction is to be carried out on the basis of the phase velocity profiles, where it is no longer necessary to determine the position of the aperture points {right arrow over (α)}_(q), but wherein it is sufficient to measure the relative movement velocity between the wave-based sensor S and the object O. This preferred modification of the previously described and already advantageous method, is a considerable simplification in the practical implementation of synthetic apertures, since it is much easier in practice, to measure velocities with slight drift errors, than distances.

The sensor S and the object O now move relative to each other at a vectorial velocity {right arrow over (v)}_(q)=|{right arrow over (v)}_(q)|·e^(jΔβq) from the q−1-th aperture point {right arrow over (α)}_(q−1) to the q-th aperture point {right arrow over (α)}_(q) with q=2, . . . Q, wherein an angle Δβ_(q) describes the angle of movement relative to the chosen reference coordinate system between two adjacent aperture points {right arrow over (α)}_(q−1) to the q-th aperture point {right arrow over (α)}_(q), i.e.:

${\cos\left( {\Delta\beta}_{q} \right)} = {\frac{x_{a,q} - x_{{aq} - 1}}{{{\overset{\rightarrow}{a}}_{q} - {\overset{\rightarrow}{a}}_{q - 1}}}.}$

The velocity vector {right arrow over (v)}_(q) can be sensed by a sensor system, such as the velocity amount by a wheel encoder, and the direction via a steering angle sensor in a vehicle. A velocity component v_(qr) in the direction of the incident angle φ_(R) is now the quantity that is reflected in a characteristic manner in the phase velocity profiles sig_(vq)(d) in the phase angle velocity ω_(q)(d). Thus, for the radial velocity component

$v_{qr} = {{{{{\overset{\rightarrow}{v}}_{q}} \cdot {\cos\left( {{\Delta\beta}_{q} - \varphi_{R}} \right)}}\mspace{14mu}{with}\mspace{14mu}{\Delta\beta}_{q}} = {\arg{\left\{ {\overset{\rightarrow}{v}}_{q} \right\}.}}}$

A phase variation f_(vqr)(φ_(RA)) i.e. a phase angle velocity ω_(q)(d) in the phase velocity profiles sig_(vq)(d) to be expected due to the measurement of the velocity v_(qr) depending on each assumed incident angle φ_(RA), is linked with the radial velocity v_(qr) via a real-value constant const_(v), and for the phase variation f_(vqr)(φ_(RA)): f _(vqr)(φ_(RA))=Const_(v) ·v _(qr).

The constant const_(v) depends on the wavelength λ and each chosen measuring principle. When a primary radar or an ultrasonic impulse echo system is used, for example,

${const}_{v} = \frac{4\pi}{\lambda}$ applies in analogy to the previous relationship with respect to the formula of the location change. In a step S6*, in a corresponding manner, a corresponding phase variation fvqr(φRA) and, therefrom, a complex phase correction value exp(−j·fvqr(φRA)) are determined.

Based on these phase velocity profiles sig_(vq)(d), in steps S7* and S8*, now, a new preferred reconstruction prescription can be defined for calculating an image function, or a probability density function W_(v)(d,φ_(RA)), as follows:

${W_{v}\left( {d,\varphi_{RA}} \right)} = {\sum\limits_{q = 1}^{Q}\;{{{sig}_{vq}(d)} \cdot {{\mathbb{e}}^{{- j} \cdot {f_{vqr}{(\varphi_{RA})}}}.}}}$

This velocity probability density function W_(v)(d,φ_(RA)) is not as easily interpreted in each case as the probability density function that was defined with the aid of the echo profiles.

In further steps S10*, the actual incident angles are then determined as follows.

For reconstruction, for each assumed angle φ_(RA), each phase velocity profile sig_(vq)(d) is now multiplied by each complex phase correction value exp(−j·f_(vqr)(φ_(RA))), and then all Q−1 thus phase corrected phase velocity profiles are summed up. The complex phase correction value results, as shown above, from the measured velocity v and the assumed angle φ_(RA) relative to the chosen reference coordinate system. If the assumed angle φ_(RA) corresponds to the actual angle to the object O, and the complex phase correction value of each complex phase correction value offsets precisely that phase value of the phase velocity profiles sig_(vq)(d) that is the phase angle velocity ω_(q)(d) so that all Q complex values are superimposed in sum for each distance d in a constructive manner. In particular, in this case, the phase angle of the resulting complex pointer in the form of the velocity probability density function W_(v)(d,φ_(RA)), at least if the velocity measurement is precise, is identical to zero. The imaginary portion of the velocity probability density function W_(v)(d,φ_(RA)), in this case, would be zero, and the real portion at a maximum.

If, however, the assumed angle φ_(RA) does not correspond to the actual incident angle φ_(R), the phases of the Q complex values are randomly distributed at curvilinear apertures in sum for each distance d. The pointers, or complex values, in the form of the velocity probability density function W_(v)(d,φ_(RA)) are thus not constructively superimposed, and the amount of the sum is substantially smaller than with the constructive superposition. With straight-line apertures, at least the phase angle of the velocity probability density function W_(v)(d,φ_(RA)) is not equal to zero, and the real portion of the sum of the velocity probability density function W_(v)(d,φ_(RA)) is substantially smaller in the case in which the assumed angle corresponds to the actual angle to the object.

For calculating an image function, the real portion of the velocity probability density function W_(v)(d,φ_(RA)) is preferably used:

${W_{v}\left( \varphi_{RA} \right)} = {{Re}\left\{ {\sum\limits_{q = 1}^{Q}\;{{{sig}_{vq}(d)} \cdot {\mathbb{e}}^{{- j} \cdot {f_{vqr}{(\varphi_{RA})}}}}} \right\}}$

A different embodiment of the evaluation can reside in calculating the angle function

${W_{v}\left( \varphi_{RA} \right)}{_{d = d_{0}}{\sum\limits_{q = 1}^{Q}\;{{{sig}_{vq}\left( d_{0} \right)} \cdot {\mathbb{e}}^{{- j} \cdot {f_{vqr}{(\varphi_{RA})}}}}}}$ for a particular distance d₀ and determining the assumed angle φ_(RA) in the function W_(v)(φ_(RA))|_(d=d) ₀ , for which the phase angle, that is the argument of W_(v)(φ_(RA))|_(d=d) ₀ becomes minimal and thus arg{W _(v)(φ_(RA)|_(d=d) ₀ }=min

In this case, in terms of probability, the assumed. angle φ_(RA) should correspond to the actual incident angle φ_(R).

A sensible assumption for the distance d₀ can often be very simply determined by determining the maximum amounts in at least one of the sensed or determined distance or velocity profiles, which are associated with certain object distances.

In FIG. 4, the relationships can be easily recognized. Plotted over the distance in meters, there is an amount of an exemplary first echo profile sig₁(d) with 4 echoes, i.e., 4 objects O or 4 transponders, in the first line, wherein the measurement was carried out at a first aperture point {right arrow over (α)}₁. The distances d of the objects O from the sensor S can be easily recognized with reference to the position of the maxima in the amount of the echo profile.

In the second line, the phase arg{sig₁(d)} of the first echo profile sig₁(d) is shown. In the third and fourth lines, the phases arg{sig₂(d)}, arg{sig₃(d)} of a second echo profile sig₂(d) sensed at a second aperture point {right arrow over (α)}₂, and a third echo profile sig₃(d) sensed at a third aperture point {right arrow over (α)}₃ are shown, respectively.

From the phases of the echo profiles sig(d), the phase angle velocities ω₁(d), ω₂(d) can then be derived in the manner described above. The phase angle velocity ω₁(d) shown in the fifth line is determined from the difference of the phases of the first echo profile sig₁(d) and the second echo profile sig₂(d). The phase angle profile velocity ω₂(d) shown in the sixth line is determined from the difference of the phases of the second echo profile sig₂(d) and the third echo profile sig₃(d).

A characteristic of the determined phase angle velocities ω₁(d), ω₂(d), extremely useful in practice, is that they are almost constant over the entire echo width, as can be clearly seen in FIG. 2. A very rough, or very imprecise detection of an object distance d₀ is thus sufficient to be able to carry out a correct incident angle determination according to the method shown. The angle measurement precision is thus not directly linked to the distance measuring precision.

The two-dimensional function of the velocity probability density functions W_(v)(d,φ_(RA)) can be transferred into a one-dimensional function, if (a) either a curvilinear aperture is present and it is assumed that two objects O are not at the same distance d or at the same actual incident angle φ_(R) in the object scene, or if (b) only one object O is in the sensing range.

Under the assumption that the phase velocity profiles sig_(vq)(d) are represented in each case in the distance range from, for example, 0-d_(max) by N scanning points, this one-dimensional probability function W_(v)(φ_(RA)) can be calculated, for example, according to

${W_{v}\left( \varphi_{RA} \right)} = {\sum\limits_{n = 1}^{N}\;{\sum\limits_{q = 1}^{Q}\;{{{sig}_{vq}\left( d_{n} \right)} \cdot {{\mathbb{e}}^{{- j} \cdot {f_{vqr}{(\varphi_{RA})}}}.}}}}$

The incident angle(s) φ_(R) at which objects O are actually present, can be recognized by the fact that the real portion of the one-dimensional probability function W_(v)(φ_(RA)) becomes maximal, or the phase angle becomes minimal when the one-dimensional probability function W_(v)(φ_(RA)) has a large value at the same time.

In practice, the velocity |{right arrow over (v)}_(q)| of the sensor S and the angle Δβ_(q) of the movement can be determined with the aid, for example, of an odometer and an angle sensor, such as a steering angle sensor, a compass or a gyroscope. With angle sensors measuring relatively and not absolutely, the angle value must be successively tracked from aperture point {right arrow over (α)}_(q) to aperture point {right arrow over (α)}_(q+1). With an absolutely measuring angle sensor system, it is sufficient to relate each angle value to a predefined common point of origin, such as the angle position at the first aperture point {right arrow over (α)}₁. A pure estimation of the angular position with respect to systems at an unknown or non-biunique distance, for which only the velocity must be known, can also be advantageously implemented.

If the moving objects O are vehicles, it can be assumed very often, for example, if the turning circle of the vehicle is great compared to the aperture, that the angle Δβ_(q) of the movement is constant, and therefore does not need to be measured. The reference coordinate system would thus be sensibly defined by the normal rolling direction of the wheels. For example, the x axis of the reference coordinate system is assumed to be fixed in the vehicle rolling direction.

Depending on the vehicle, it can also be suitable to assume that the velocity |{right arrow over (v)}_(q)| is constant during the Q measurements, as is described in the following.

As an extension of the explanations above, a number Q−2 of phase acceleration profiles sig_(aq)(d) can also be formed, for example, from the number Q of the echo profile or the number Q−1 of the phase velocity profiles. The phase acceleration profiles sig_(aq)(d) give an indication on the change in velocity, i.e. on the absolute radial acceleration of the sensor S. The phase angle acceleration α_(q)(d) as the argument of the phase acceleration profile sig_(aq)(d) now results in

${\alpha_{q}(d)} = {\frac{{\omega_{q}(d)} - {\omega_{q - 1}(d)}}{\Delta\; T_{q}}.}$

The phase acceleration profiles sig_(aq)(d) can be calculated, in analogy to the previous explanation for the phase velocity profile sig_(vq)(d), preferably as follows: h _(aq)(d)=sig _(vq)(d)·sig _(vq−1)(d). and sig _(aq)(d)=|h _(aq)(d)|·e ^(j·α) ^(q) ^((d)) with the phase angle acceleration:

${\alpha_{q}(d)} = {\frac{\arg\left\{ {h_{aq}(d)} \right\}}{\Delta\; T_{q}}.}$

The phase acceleration profiles sig_(aq)(d) can of course also be established, just like the phase velocity profiles sig_(vq)(d) with respect to the amount in an unsquared manner, and the other remarks with respect to the amounts apply in the same way.

The sensor S and the object O now move relative to each other at the acceleration vector {right arrow over (α)}_(q)=|{right arrow over (α)}_(q)|·e^(jΔβ) ^(q) , wherein the angle Δβ_(q) describes the angle of the acceleration vector relative to the chosen reference coordinate system.

The acceleration vector {right arrow over (α)}_(q) can be sensed, for example, by a sensor system, for example by Micro-Electro-Mechanical-Systems (MEMS), acceleration sensors and gyroscopes. The acceleration component α_(qr) in the direction of the incident angle φ_(R) is now the quantity that has an effect on the phase acceleration profiles sig_(aq)(d) in the phase angle acceleration α_(q)(d) in a characteristic manner. For the radial acceleration component: α_(qr)=|{right arrow over (α)}_(q)|·cos(Δβ_(q)−φ_(R)) with Δβ_(q) =arg{{right arrow over (α)} _(q)}.

A phase variation f_(aqr)((φ_(RA)), i.e. the phase angle velocity to be expected on the basis of the measurement of the acceleration {right arrow over (α)}_(q), depending on each assumed incident angle φ_(RA) in the phase velocity profiles sig_(aq)(d), is linked with the radial acceleration α_(qr) via a real-value constant const_(a), and it applies: f _(aqr)(φ_(RA))=const_(a)·^(α) ^(qr)

The constant const_(a) depends on the wavelength λ and each selected measuring principle, in analogy to the explanations with respect to the velocity and distance.

Based on these phase acceleration profiles sig_(aq)(d), a further reconstruction prescription can be defined as follows:

${W_{a}\left( {d,\varphi_{RA}} \right)} = {\sum\limits_{q = 1}^{Q}\;{{{sig}_{ag}(d)} \cdot {{\mathbb{e}}^{{- j} \cdot {f_{aqr}{(\varphi_{RA})}}}.}}}$

The evaluation of this image function, or acceleration probability distribution W_(a)(d,φ_(RA)) is made including all evaluation variants in analogy to the evaluation of the image function determined with the aid of the phase velocity profiles.

For reconstruction, each phase acceleration profile sig_(aq)(d) is thus multiplied with the respective complex phase correction value exp(−j f_(aqr)(φ_(RA))) for each assumed angle φ_(RA), and then all Q−2 thus phase corrected phase acceleration profiles are summed up.

In an analogous fashion, as has already been explained for the distance holography above, the two-dimensional function as the acceleration probability distribution W_(a)(d,φ_(RA)) can be separated into two one-dimensional functions W_(a)(φ_(RA)) or W_(a)(d).

Particularly advantageously, it can also be applied in this case that the phase angle acceleration α_(q)(d), just as shown in FIG. 4 for the phase angle velocities ω_(q)(d), is almost constant over the entire echo width in a phase acceleration profile sig_(aq)(d). Consequently, it is also suitable in the present case to apply the reconstruction formula not for all distances d, but in a selective manner only for those distances in which echoes/objects are recognizable in the contributions of the profiles. A consequence for this case is the simplified function for angle estimation as a one-dimensional acceleration probability distribution according to the following:

${W_{a}\left( \varphi_{RA} \right)}{_{d = d_{0}}{\sum\limits_{q = 1}^{Q}\;{{{sig}_{aq}\left( d_{0} \right)} \cdot {{\mathbb{e}}^{{- j} \cdot {f_{aqr}{(\varphi_{RA})}}}.}}}}$

It should be noted at this stage that the one-dimensional acceleration probability distribution W_(a)(φ_(RA))|_(d=d0) often has a systematic, in particular a sinusoidal, characteristic. In this case it is possible, after the calculation of a few values of the one-dimensional acceleration probability distribution W_(a)(φ_(RA))|_(d=d0), to determine the value of the angle φ_(RA) in an analytical manner, at which the amount or real portion of the one-dimensional acceleration probability distribution W_(a)(φ_(RA))|_(d=d0) is at a maximum, or at which the phase angle, that is the argument of the one-dimensional acceleration probability distribution W_(a)(φ_(RA))|_(d=d0), becomes equal to zero, that is at which the assumed angle φ_(RA) corresponds to the actual angle φ_(R). It is thus no longer necessary to vary φ_(RA) step by step over the entire angle range and to determine the above mentioned extreme values of the one-dimensional acceleration probability distribution W_(a)(φ_(RA))|_(d=d0), or the zero crossing of the phase of the one-dimensional acceleration probability distribution W_(a)(φ_(RA))|_(d=d0) by a search function. The possibility of the analytic calculation of the above mentioned extreme values of the one-dimensional acceleration probability distribution W_(a)(φ_(RA))|_(d=d0), or the zero crossing of the phase of the one-dimensional acceleration probability distribution W_(a)(φ_(RA))|_(d=d0), consequently offers the possibility of a substantial reduction of the computation overhead.

The same approach would, of course, be possible in correspondence to the above extension, if the phase angle velocities were used.

In practice, the acceleration and the angle acceleration could be determined, for example, by way of MEMS acceleration sensors and gyroscopes, wherein these quantities could be converted into |{right arrow over (α)}_(q)| and Δβ_(q), by way of mathematical functions known as such. Preferably, the direction of the acceleration is successively tracked starting with the first aperture point {right arrow over (α)}₁, from aperture point {right arrow over (α)}_(q) to aperture point {right arrow over (α)}_(q+1) by way of a gyroscope.

The particular advantage of the method is that in practice it is much easier to measure accelerations with small drift errors than velocities or distances. This advantage is particularly noticeable in hand-held radio systems. If a transponder carried by a human or a wave-based measuring system carried by a human, which measures a cooperative transponder, such as a landmark, is equipped with acceleration sensors, it is very simple to determine the distance and the angular position of the sensor with respect to the transponder, and thus the position. The idea presented here is therefore particularly suitable, for example, for indoor navigation systems or even for hand-held RFID readers with the ability to determine the position of the RFID tags relative to the reader.

For a vehicle with a large turning circle, or an object moving almost in a straight line, and in particular for a rail or path-guided vehicle or transport mechanism, the use of gyroscopes can be dispensed with, if the phase angle acceleration α_(q)(d) in the phase acceleration profiles sig_(aq)(d) that is caused by the rotatory acceleration of the vehicle, is small.

The suggested approach can analogously be applied to further quantities generated by way of differentiation from the velocity and acceleration.

All explanations given in a simplified manner with reference to two-dimensional arrangements for reasons of clarity, can also be transferred to three-dimensional problems by way of geometric considerations.

The method described can be used in many applications: for estimating the angle at which targets are present, such as transponders, RFID tags, that do not allow good distance measurement; in vehicles in order to use a method adapted to the properties of the sensor system present (drift, low precision); and in position determination by way of local radio locating systems and GPS; but also for use in imaging, collision avoidance or navigation with primary radars or ultrasonic sensors.

The system or systems described herein may be implemented on any form of computer or computers and the components may be implemented as dedicated applications or in client-server architectures, including a web-based architecture, and can include functional programs, codes, and code segments. Any of the computers may comprise a processor, a memory for storing program data and executing it, a permanent storage such as a disk drive, a communications port for handling communications with external devices, and user interface devices, including a display, keyboard, mouse, etc. When software modules are involved, these software modules may be stored as program instructions or computer readable codes executable on the processor on a computer-readable media such as read-only memory (ROM), random-access memory (RAM), CD-ROMs, magnetic tapes, floppy disks, and optical data storage devices. The computer readable recording medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion. This media can be read by the computer, stored in the memory, and executed by the processor.

All references, including publications, patent applications, and patents, cited herein are hereby incorporated by reference to the same extent as if each reference were individually and specifically indicated to be incorporated by reference and were set forth in its entirety herein.

For the purposes of promoting an understanding of the principles of the invention, reference has been made to the preferred embodiments illustrated in the drawings, and specific language has been used to describe these embodiments. However, no limitation of the scope of the invention is intended by this specific language, and the invention should be construed to encompass all embodiments that would normally occur to one of ordinary skill in the art.

The present invention may be described in terms of functional block components and various processing steps. Such functional blocks may be realized by any number of hardware and/or software components configured to perform the specified functions. For example, the present invention may employ various integrated circuit components, e.g., memory elements, processing elements, logic elements, look-up tables, and the like, which may carry out a variety of functions under the control of one or more microprocessors or other control devices. Similarly, where the elements of the present invention are implemented using software programming or software elements the invention may be implemented with any programming or scripting language such as C, C++, Java, assembler, or the like, with the various algorithms being implemented with any combination of data structures, objects, processes, routines or other programming elements. Functional aspects may be implemented in algorithms that execute on one or more processors. Furthermore, the present invention could employ any number of conventional techniques for electronics configuration, signal processing and/or control, data processing and the like. The words “mechanism” and “element” are used broadly and are not limited to mechanical or physical embodiments, but can include software routines in conjunction with processors, etc.

The particular implementations shown and described herein are illustrative examples of the invention and are not intended to otherwise limit the scope of the invention in any way. For the sake of brevity, conventional electronics, control systems, software development and other functional aspects of the systems (and components of the individual operating components of the systems) may not be described in detail. Furthermore, the connecting lines, or connectors shown in the various figures presented are intended to represent exemplary functional relationships and/or physical or logical couplings between the various elements. It should be noted that many alternative or additional functional relationships, physical connections or logical connections may be present in a practical device. Moreover, no item or component is essential to the practice of the invention unless the element is specifically described as “essential” or “critical”.

The use of “including,” “comprising,” or “having” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. Unless specified or limited otherwise, the terms “mounted,” “connected,” “supported,” and “coupled” and variations thereof are used broadly and encompass both direct and indirect mountings, connections, supports, and couplings. Further, “connected” and “coupled” are not restricted to physical or mechanical connections or couplings.

The use of the terms “a” and “an” and “the” and similar referents in the context of describing the invention (especially in the context of the following claims) are to be construed to cover both the singular and the plural. Furthermore, recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein, and each separate value is incorporated into the specification as if it were individually recited herein. Finally, the steps of all methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., “such as”) provided herein, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed. Numerous modifications and adaptations will be readily apparent to those skilled in this art without departing from

List of Reference Numerals: {right arrow over (α)}_(q) = (x_(aq), y_(aq))^(T) aperture points, q = 1, 2, . . . , Q {right arrow over (α)}_(q) vectorial acceleration α_(qr) acceleration component in the direction of the incident angle φ_(R) B measuring signal bandwidth of the signals, or wave c propagation velocity of the signals, or wave c* phase velocity of the signals const. real-value constant, depending on the measuring principle C controller d, d_(q) instantaneous distance of the object at the q-th aperture point from the sensor d_(R) reference distance from object O to the first aperture point f_(vqr)(φ_(RA)) phase variation for velocity correction f_(aqr)(φ_(RA)) phase variation for acceleration correction K maximum number of discrete angle values M memory O object/transponder p({right arrow over (r)}) object position q serial index for 1, 2, . . . , Q Q number of measurements/aperture points {right arrow over (r)} = (x, y)^(T) space coordinate rs signal coming from object O s signal from sensor S sensor sig_(q)(d) echo profiles sig_(q)(d, φ_(RA)) shifted echo profiles sig_(q)(d, φ_(RA))” adapted echo profiles sumsig(d, sum profile across all aperture points φ_(RA)) sig_(vq)(d) phase velocity profiles sig_(aq)(d) phase acceleration profiles v, {right arrow over (v)}_(q) velocity V apparatus W(d, φ_(RA)) measure for the probability W(φ_(RA)) measure for the probability of the incident angle W(d) measure for the probability of the object distance W_(v)(d, φ_(RA)) velocity probability density function W_(v)(φ_(RA)) one-dimensional probability function W_(a)(d, φ_(RA)) acceleration probability distribution W_(a)(φ_(RA)) one-dimensional acceleration probability distribution x, y, z space coordinates α_(q)(d) phase angle acceleration β_(q) reference angle between coordinate systems Δβ_(q) angle of movement Δa_(q) distance between two aperture points Δd_(q)(φ_(R)) lateral distance transverse to the wave propagation direction as distance change of the transmission path from the sensor to the object from aperture point {right arrow over (α)}₁ to aperture point {right arrow over (α)}_(q) Δd_(q)(φ_(RA)) assumed lateral distance ΔT_(q) time interval between measurements λ wavelength of signal φ_(q)(d) phase angle of signal φ_(R) incident angle of the planar waves φ_(RA) assumed angle, at which the object is apparently seen φ_(RAK) discrete angle values of the angle range covered ω circle center frequency of the waveform/signals used ω_(q)(d) phase angle velocity 

1. An imaging method with a synthetic aperture for determining at least one of an incident angle and a distance of a sensor from at least one object in space, comprising: sensing, at a number of aperture points, one respective echo profile; calculating at least one of one phase correction value and one distance correction value for each of a plurality of assumed angles as the at least one incident angle; generating adapted profiles based the echo profiles by at least one of adapting the phase by the phase correction value for each of the assumed angles and shifting the distance by the distance correction value; forming a probability distribution for the assumed angles from the adapted profiles; and determining at least one of a probability value for the incident angle and the distance from the probability distribution.
 2. The method according to claim 1, further comprising: summing up or integrating, for the assumed angles, the adapted profiles; and forming the probability distribution therefrom.
 3. The method according to claim 1, further comprising calculating at least one of the phase correction values and the distance correction values on the basis of the aperture points from the position data of the aperture.
 4. The method according to claim 1, further comprising generating an adapted echo profile as the adapted profile by at least one of adapting the phase of the echo profiles for each assumed angle by the phase correction value and shifting the distance by the distance correction value.
 5. The method according to claim 1, further comprising separating the probability function into one-dimensional probability functions by summing-up or by determining maxima.
 6. The method according to claim 1, further comprising: forming a number of phase velocity profiles from the echo profiles; and determining phase angle velocities as their argument.
 7. The method according to claim 6, further comprising calculating the at least one angle assumed as the incident angle in dependence on a relative movement velocity between the wave-based sensor and the object and, in each case, calculating one complex phase correction value as a correction in dependence on a phase variation based on a velocity difference.
 8. The method according to claim 6, further comprising summing up or integrating, for each assumed angle, the phase-corrected phase velocity profiles are summed-up or integrated to form velocity probability density functions.
 9. The method according to claim 1, further comprising calculating the at least one angle assumed as the incident angle in dependence on a relative acceleration between the wave-based sensor and the object, and, in each case, calculating one complex phase correction value as a correction in dependence on a phase variation based on an acceleration difference.
 10. The method according to claim 9, further comprising: forming a number of phase acceleration profiles from the echo profiles; and determining an acceleration vector as their argument.
 11. The method according to claim 9, further comprising summing of or integrating, for each assumed angle, the phase-corrected phase acceleration profiles to form an acceleration probability distribution.
 12. The method according to claim 9, further comprising performing an analytical calculation of the extreme values of the one-dimensional acceleration probability distribution or of the zero crossing of the phase of the one-dimensional acceleration probability distribution.
 13. The method according to claim 1, further comprising, for sensing the echo profile, transmitting a signal from the sensor to the at least one object, and the at least one object in space includes a transponder, or is configured as a transponder, which receives the signal and transmits a modified signal in dependence on the signal as a signal coming from the object, back to the sensor, which is used as a signal received in the sensor as the echo profile.
 14. An apparatus comprising a wave-based sensor for sensing a sequence of echo signals of an object, and comprising at least one of a logic element and a processor that accesses at least one program as a controller, wherein at least one of the logic and the processor is configured for carrying out a method according to claim 1 for determining at least one of an incident angle and a distance of a sensor from at least one object in space.
 15. The apparatus according to claim 14, comprising a memory or an interface to a memory, wherein the program is stored in the memory.
 16. The apparatus according to claim 14, wherein the object includes a transponder or is configured as a transponder. 